I work at the intersection of geospatial analysis, atmospheric data, and public health — building the evidence base that links pollution, climate, and demographic risk to real-world decisions.
I'm drawn to work that answers a concrete "so what" — not just whether a method or model works in principle, but what it changes for the decisions and people it's meant to serve.
My background spans a BSc in Geography, an MSc in GIS & Environmental Management, and a PhD researching the impacts of air quality interventions — including ULEZ and COVID-19 traffic reductions — on ultrafine particles and secondary pollutants, alongside the atmospheric chemistry of hydrogen combustion as a fuel-switching pathway.
Current work spans regional solar suitability mapping, air quality and health equity analysis, and open-source tooling for meteorological normalisation of air quality data.
Lead geospatial analyst on a site-suitability assessment across East and West Sussex for ground-mounted and rooftop solar with battery storage — integrating environmental, heritage, agricultural, infrastructure, and terrain constraints into a scored raster surface, delivered via an interactive Shiny mapping tool.
Linking modelled pollution surfaces with deprivation indices and health outcome data to identify where environmental risk and social vulnerability overlap, supporting research and policy dissemination.
Technical lead on emissions sampling feasibility and monitoring strategy for a £1.17m NZIP-funded project assessing hydrogen as an alternative to natural gas in crematoria, from funding-bid stage through on-site equipment deployment and stakeholder training.
PhD thesis (University of Leicester, CENTA-NERC funded) assessing how interventions such as ULEZ, COVID-19 traffic reductions, and hydrogen fuel-switching alter atmospheric chemistry and secondary pollutant formation. Includes deweatherXGB, an open-source R package extending David Carslaw's deweather with XGBoost-based meteorological normalisation for air quality time series.
Real analysis, reformatted from doctoral research.
Meteorological normalisation of NO₂ trends — the detrended series (left) strips out weather-driven noise from the raw observed series (right) using deweatherXGB, making the underlying ULEZ/COVID-19 intervention effect on NO₂ concentration clearly visible. Adapted from Figure 3-7 of my PhD thesis, University of Leicester (2026). Read the thesis · Read the paper
Open to freelance and consultancy work across environmental data science, geospatial analysis, and demographic data. Send a few details and I'll get back to you.
Submissions are processed via Formspree and used only to respond to your enquiry. If you'd rather not use the form, reach out directly via email.